One of the biggest challenges for marketers new to Marketing Cloud Engagement is the need to steer away from simple subscriber lists and instead make use of Data Extensions and other more advanced data modelling because some features of Marketing Cloud, such as Journey Builder, require it.
Kumar Gurrampalli
4 mins
If you’ve dug around the system, you’ve no doubt come up against a number of strange terms and if you’ve charged forward and attempted to create your data model already, perhaps you’re seeing duplicate contacts as a result.
This isn’t uncommon! We speak with many users who are lumbered with Marketing Cloud Engagement when joining a new company or following a basic implementation. Often, they’ve been plowing their way through, trying to successfully pull in data sources and set up journeys single-handedly. The result is confusion, many hours of troubleshooting, and an unreliable database.
Creating a data model can be complicated, especially if you’re not familiar with best practices.
Allow us to remove some of the headaches for you with this basic introduction to the key terms and steps.
Firstly, it’s important to learn the basic words and phrases you’ll encounter when managing data in Marketing Cloud.
| Term | Definition |
| Relational data | A relational database stores multiple tables of data that are related to each other. For example, a single ecommerce transaction may use multiple tables to store billing information, shipping details, and customer profile values separately, yet these tables are all related. |
| Data Extension | Data Extensions are the Marketing Cloud version of tables used to store information about your contacts. They’re different to subscriber lists in that Data Extensions collate relational information about a person in one place, with a unique piece of identifiable information to tie it together. One contact can exist in multiple Data Extensions. |
| Data source |
A data source is any place you collect information about a contact, whether it’s your website, an app, social media messages, POS system, a third-party website, and so on. Data sources can be integrated with Marketing Cloud using out-of-the-box connectors or via API, allowing you to import contact data. |
| Primary key / Contact key |
In data modelling, a primary or contact key is the column containing the unique value that allows you to identify a single customer. This is often their email address but can be any unique value. |
| Contact Builder |
A Marketing Cloud module that allows you to visualise and manage your data model and contacts. |
| Data Designer | Data Designer is a feature within the Contact Builder module in Marketing Cloud. Like the name says, it’s where you design your data by mapping and linking your Data Extensions and their values. |
| Attributes | In Marketing Cloud, attributes are essentially field values. An attribute can be any piece of data about a contact, including profile attributes i.e. a way of identifying the contact such as their name, email, date of birth etc., and behaviour attributes i.e. interactions and engagements such as email opens and clicks. |
| Attribute Groups | Attribute Groups are how you group related tables of data. You create Attribute Groups using Data Designer and link the attributes you want to include in your journeys. Marketing Cloud comes with system-defined Attribute Groups that can be modified but not deleted. You can also set up Attribute Groups from scratch and these are known as ‘User-defined Attribute Groups’. |
Once you have your head around the jargon, you can begin planning your own data model. Note I said planning, not building… yet!
Start with these steps:
List all of the data sources you have.
List all of the field values (attributes) you collect using these sources.
Consider which you want to store and use, and which you can ignore/
Use a visual diagram to map out how you want to group your data i.e. one table for shipping information, one table for customer purchase history, one table for basic customer details, etc.
Decide which attribute will be your primary / contact key - what’s the single unique value that identifies a contact?
By the end of this process, you should be able to visualise how many Data Extensions you’ll need, which columns and attributes they’ll contain, and how each is related to the others, along with the primary key that identifies the same customer across all of the Data Extensions.
In essence, you’ve designed your data model!
Once you have a clearly defined plan, you can jump into Contact Builder and start creating your Marketing Cloud data model.
At this stage, you should:
Integrate your various data sources but don’t import data just yet.
Setup your Data Extensions and their attributes.
Create an Attribute Group in Data Designer and link the Data Extensions and attributes to be included, along with the primary / contact key. If you miss this step, you won’t be able to use the attributes in Journey Builder decisions.
Import your contact data to the relevant Data Extensions.
Clearly define your marketing objectives and goals. Recognise the critical metrics and data points for your marketing strategy.
To create a single customer profile, combine data from various sources (website, CRM, social media, etc.). This enables personalised marketing efforts and a more in-depth understanding of customer behaviour.
Establish stringent data quality and governance standards. Ensure that the data is accurate, consistent, and complete. Implement processes to clean and validate data regularly to maintain a high level of quality.
Prioritise data security and regulatory compliance (e.g., GDPR, CCPA). To protect sensitive customer information, use encryption, access controls, and other security measures.
Create a customer journey that takes them from awareness to conversion and beyond. Determine touchpoints and interactions across multiple channels. This knowledge will assist you in defining the data entities and relationships required to track and analyse customer behaviour.
Create a data model that will grow with your company. Think about future data volume increases and make sure your infrastructure and architecture can handle the growing dataset without sacrificing performance.
Integrate powerful analytics and reporting capabilities into your data model. This enables marketing teams to gain actionable insights and assess the efficacy of their campaign.
Hopefully, this blog post has put you on the right track to creating a Marketing Cloud data model but if you’re feeling overwhelmed, or you’re already stuck with database issues and need a helping hand, we have the perfect solution.
Take a look at our Marketing Cloud database management service and get in touch today.
Kumar’s working day involves end-to-end Salesforce Marketing Cloud Engagement implementations & API integrations. Typical tasks include requirement gathering, solution design, testing, implementation, and overseeing the development. He’s quality-focused and always gives best-in-class solutions to clients.
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